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Part Time Remote Data Labelling Jobs in Phoenix, AZ

Job Title: AI Finance Domain Expert Job Type: Contractor (Part-Time) Location: Remote Job Overview We are seeking experienced AI Finance Domain Experts to contribute their financial expertise to an

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Part Time Remote Data Labelling information

See Phoenix, AZ salary details

$45.7K

$163.8K

$241.8K

How much do part time remote data labelling jobs pay per year?

As of Sep 13, 2026, the average yearly pay for part time remote data labelling in Phoenix, AZ is $163,848.00, according to ZipRecruiter salary data. Most workers in this role earn between $132,600.00 and $168,800.00 per year, depending on experience, location, and employer.

What is a part time remote data labelling job?

A part time remote data labelling job involves annotating or tagging data—such as images, text, or audio—from your own location, typically using specialized software provided by employers. The role is essential for training machine learning models, as accurate labels help computers learn to recognize patterns. These jobs are often flexible, allowing you to set your own hours and work from anywhere with an internet connection. No advanced technical skills are usually required, but attention to detail is important.

What are the key skills and qualifications needed to thrive as a part time remote data labelling specialist?

To excel as a Part Time Remote Data Labelling specialist, you need strong attention to detail, basic computer literacy, and a solid understanding of data privacy and handling protocols, often requiring a high school diploma or equivalent. Familiarity with annotation platforms, spreadsheet software, and sometimes specific data labelling tools like Labelbox or Supervisely is typically required. Reliability, time management, and clear communication are crucial soft skills for meeting deadlines and collaborating in a remote setting. These skills and qualities ensure that labelled data is accurate, consistent, and valuable for training effective machine learning models.

What are some common challenges faced by part time remote data labelling professionals, and how can they be managed?

Part-time remote data labellers often face challenges such as maintaining consistent accuracy, staying focused during repetitive tasks, and managing communication with a distributed team. To address these, it’s helpful to establish a quiet, distraction-free workspace, use productivity techniques like the Pomodoro method, and regularly review labelling guidelines to minimize errors. Leveraging communication tools and participating in team check-ins can also help clarify questions and build a sense of connection with colleagues.

What is the difference between Part Time Remote Data Labelling vs Part Time Remote Data Annotation?

AspectPart Time Remote Data LabellingPart Time Remote Data Annotation
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote, flexible hoursRemote, flexible hours
Industry UsageAI, machine learning, data processingAI, machine learning, data processing
Job FocusLabeling data for training AI modelsAnnotating data for AI training

Part Time Remote Data Labelling and Part Time Remote Data Annotation are similar roles involving preparing data for AI systems. Labelling typically involves categorizing data, while annotation may include adding detailed notes or markings. Both roles require attention to detail and are performed remotely, making them suitable for flexible schedules. The main difference lies in the specific tasks, but they are often used interchangeably depending on the employer or project.

What are the most commonly searched types of Remote Data Labelling jobs in Phoenix, AZ?

The most popular types of Remote Data Labelling jobs in Phoenix, AZ are:

What job categories do people searching Part Time Remote Data Labelling jobs in Phoenix, AZ look for?

The top searched job categories for Part Time Remote Data Labelling jobs in Phoenix, AZ are:

AI Finance Expert - Remote

Phoenix, AZ • Remote

$100 - $200/hr

Part-time

Re-posted 3 days ago


Job description

Job Title: AI Finance Domain Expert

Job Type: Contractor (Part-Time)
Location: Remote

Job Overview

We are seeking experienced AI Finance Domain Experts to contribute their financial expertise to an innovative project at the intersection of finance and artificial intelligence. In this role, you will help improve next-generation AI systems by reviewing, evaluating, and refining AI-generated financial content. No prior AI experience is required—your financial expertise, analytical skills, and professional judgment are what matter most.

Key Responsibilities
  • Analyze, review, and edit AI-generated financial content for accuracy, clarity, and relevance.

  • Develop, refine, and evaluate prompts related to financial analysis, valuation, and investment decision-making.

  • Assess and annotate financial data, reports, and AI-generated outputs using structured evaluation criteria.

  • Author and review investment memos, due diligence reports, research summaries, and technical documentation.

  • Evaluate AI outputs for logical consistency, factual accuracy, and adherence to professional financial standards.

  • Conduct independent research and fact-checking to validate financial information.

  • Provide detailed feedback to improve AI model performance and financial reasoning.

Required Skills
  • Critical Thinking

  • Analytical Reasoning

  • Quality Assurance

  • Prompt Engineering

  • AI Output Evaluation

  • Financial Analysis

  • Technical & Report Writing

  • Business Communication

  • Content Review & Editing

  • Fact Checking

  • Data Interpretation

  • Data Annotation

  • Problem-Solving

  • Independent Research

  • Attention to Detail

Preferred Qualifications
  • Minimum 3 years of experience in private equity, venture capital, investment banking, equity research, corporate development, investment management, or strategic finance.

  • Experience preparing investment memos, valuation analyses, financial models, due diligence reports, or market research.

  • Strong analytical, critical thinking, and problem-solving skills.

  • Excellent written communication and professional editing abilities.

  • Experience with prompt authoring, AI output evaluation, data annotation, or content review is a plus.

  • Master's, MBA, JD, PhD, or another advanced degree is preferred.

  • Commitment to producing high-quality, accurate, and well-documented work.